int suggest(t_sh *sh, char *cmd)
{
t_suggest sugg;
sugg.nb_bin = 0;
sugg.dist_min = -1;
if (!cmd)
return (0);
if (!(sugg.binaries = malloc(sizeof(char *) * 1)))
return (1);
sugg.binaries[0] = NULL;
if (check_all_path(sh, &sugg) == 1)
return (1);
if (!(sugg.tab_dist = malloc(sizeof(int) * sugg.nb_bin)))
return (1);
calc_all_distances(&sugg, cmd);
print_minimal_dist(&sugg, 0, 0);
free_datas(&sugg);
return (0);
}
void kmeans(
int dim, // dimension of data
double *X, // pointer to data
int n, // number of elements
int k, // number of clusters
double *cluster_centroid, // initial cluster centroids
int *cluster_assignment_final // output
)
{
double *dist = (double *)malloc(sizeof(double) * n * k);
int *cluster_assignment_cur = (int *)malloc(sizeof(int) * n);
int *cluster_assignment_prev = (int *)malloc(sizeof(int) * n);
double *point_move_score = (double *)malloc(sizeof(double) * n * k);
if (!dist || !cluster_assignment_cur || !cluster_assignment_prev || !point_move_score)
fail("Error allocating dist arrays");
// initial setup
calc_all_distances(dim, n, k, X, cluster_centroid, dist);
choose_all_clusters_from_distances(dim, n, k, dist, cluster_assignment_cur);
copy_assignment_array(n, cluster_assignment_cur, cluster_assignment_prev);
// BATCH UPDATE
double prev_totD = BIG_double;
int batch_iteration = 0;
while (batch_iteration < MAX_ITERATIONS)
{
// printf("batch iteration %d \n", batch_iteration);
// cluster_diag(dim, n, k, X, cluster_assignment_cur, cluster_centroid);
// update cluster centroids
calc_cluster_centroids(dim, n, k, X, cluster_assignment_cur, cluster_centroid);
// deal with empty clusters
// XXXXXXXXXXXXXX
// see if we've failed to improve
double totD = calc_total_distance(dim, n, k, X, cluster_centroid, cluster_assignment_cur);
if (totD > prev_totD)
// failed to improve - currently solution worse than previous
{
// restore old assignments
copy_assignment_array(n, cluster_assignment_prev, cluster_assignment_cur);
// recalc centroids
calc_cluster_centroids(dim, n, k, X, cluster_assignment_cur, cluster_centroid);
printf(" negative progress made on this step - iteration completed (%.2f) \n", totD - prev_totD);
// done with this phase
break;
}
// save previous step
copy_assignment_array(n, cluster_assignment_cur, cluster_assignment_prev);
// move all points to nearest cluster
calc_all_distances(dim, n, k, X, cluster_centroid, dist);
choose_all_clusters_from_distances(dim, n, k, dist, cluster_assignment_cur);
int change_count = assignment_change_count(n, cluster_assignment_cur, cluster_assignment_prev);
printf("%3d %u %9d %16.2f %17.2f\n", batch_iteration, 1, change_count, totD, totD - prev_totD);
fflush(stdout);
// done with this phase if nothing has changed
if (change_count == 0)
{
printf(" no change made on this step - iteration completed \n");
break;
}
prev_totD = totD;
batch_iteration++;
}
cluster_diag(dim, n, k, X, cluster_assignment_cur, cluster_centroid);
// ONLINE UPDATE
/* The online update prtion of this code has never worked properly, but batch update has been adequate for our projects so far.
int online_iteration = 0;
int last_point_moved = 0;
int cluster_changed[MAX_CLUSTERS];
for (int ii = 0; ii < k; ii++)
cluster_changed[ii] = 1;
int cluster_member_count[MAX_CLUSTERS];
get_cluster_member_count(n, k, cluster_assignment_cur, cluster_member_count);
while (online_iteration < MAX_ITERATIONS)
{
// printf("online iteration %d \n", online_iteration);
// for each cluster
for (int ii = 0; ii < k; ii++)
if (cluster_changed[ii])
update_delta_score_table(dim, n, k, X, cluster_assignment_cur, cluster_centroid, cluster_member_count, point_move_score, ii);
// pick a point to move
// look at points in sequence starting at one after previously moved point
int make_move = 0;
int point_to_move = -1;
int target_cluster = -1;
for (int ii = 0; ii < n; ii++)
{
int point_to_consider = (last_point_moved + 1 + ii) % n;
// find the best target for it
int best_target_cluster = -1;
int best_match_count = 0;
double best_delta = BIG_double;
// for each possible target
for (int jj = 0; jj < k; jj++)
{
double cur_delta = point_move_score[point_to_consider*k + jj];
// is this the best move so far?
if (cur_delta < best_delta)
// yes - record it
{
best_target_cluster = jj;
best_delta = cur_delta;
best_match_count = 1;
}
else if (cur_delta == best_delta)
// no, but it's tied with the best one
best_match_count++;
}
// is the best cluster for this point its current cluster?
if (best_target_cluster == cluster_assignment_cur[point_to_consider])
// yes - don't move this point
continue;
// do we have a unique best move?
if (best_match_count > 1)
// no - don't move this point (ignore ties)
continue;
else
// yes - we've found a good point to move
{
point_to_move = point_to_consider;
target_cluster = best_target_cluster;
make_move = 1;
break;
}
}
if (make_move)
{
// where should we move it to?
printf(" %10d: moved %d to %d \n", point_to_move, cluster_assignment_cur[point_to_move], target_cluster);
// mark which clusters have been modified
for (int ii = 0; ii < k; ii++)
cluster_changed[ii] = 0;
cluster_changed[cluster_assignment_cur[point_to_move]] = 1;
cluster_changed[target_cluster] = 1;
// perform move
perform_move(dim, n, k, X, cluster_assignment_cur, cluster_centroid, cluster_member_count, point_to_move, target_cluster);
// count an iteration every time we've cycled through all the points
if (point_to_move < last_point_moved)
online_iteration++;
last_point_moved = point_to_move;
}
}
*/
// printf("iterations: %3d %3d \n", batch_iteration, online_iteration);
// write to output array
copy_assignment_array(n, cluster_assignment_cur, cluster_assignment_final);
free(dist);
free(cluster_assignment_cur);
free(cluster_assignment_prev);
free(point_move_score);
}
